arXiv subjects

John T. Stefan

Publications and source records attributed to John T. Stefan.

9 recordsLinked to original sources

arXiv2026

Time-Dependence of Subsurface Solar Convection Using the Time-Distance Deep-Focus Method

We re-examine the deep-focus methodology of time-distance helioseismology previously used to estimate the power spectrum of the solar convection at a depth of about 30 Mm, which was found to be significantly weaker than predicted by theory and simulations. The Global Acoustic, Linearized Euler (GALE) and Eulerian Lagrangian (EULAG) codes are used to generate ground-truth simulations to evaluate the accuracy of the inferred convective power spectrum. This validation process shows that the power spectrum derived using the time-distance methodology diverges significantly from ground truth beyond spatial scales corresponding to the spherical harmonic degree $\ell=15$--$30$ because of the limited resolution of helioseismic measurements at that depth. However, the power estimated at larger spatial scales ($\ell<15$) is sufficiently accurate. We then apply the methodology to solar data selected from throughout Solar Cycle 24 and find some evidence that the magnitude of the convective power changes throughout the Cycle. An average of the convective power across the Solar Cycle reveals a spectrum that is qualitatively similar to previous estimates, though about half an order of magnitude greater. The disagreement between observations of solar convection and the magnitudes predicted by simulations persists.

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arXiv2026

SolARED: Solar Active Region Emergence Dataset for Machine Learning Aided Predictions

The development of accurate forecasts of solar eruptive activity has become increasingly important for preventing potential impacts on space technologies and exploration. Therefore, it is crucial to detect Active Regions (ARs) before they start forming on the solar surface. This will enable the development of early-warning capabilities for upcoming space weather disturbances. For this reason, we prepared the Solar Active Region Emergence Dataset (SolARED). The dataset is derived from full-disk maps of the Doppler velocity, magnetic field, and continuum intensity, obtained by the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). SolARED includes time series of remapped, tracked, and binned data that characterize the evolution of acoustic power of solar oscillations, unsigned magnetic flux, and continuum intensity for 50 large ARs before, during, and after their emergence on the solar surface, as well as surrounding areas observed on the solar disc between 2010 and 2023. The resulting ML-ready SolARED dataset is designed to support enhancements of predictive capabilities, enabling the development of operational forecasts for the emergence of active regions. The SolARED dataset is available at https://sun.njit.edu/sarportal/, through an interactive visualization web application.

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arXiv2024

Solar Active Regions Emergence Prediction Using Long Short-Term Memory Networks

We developed Long Short-Term Memory (LSTM) models to predict the formation of active regions (ARs) on the solar surface. Using the Doppler shift velocity, the continuum intensity, and the magnetic field observations from the Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI), we have created time-series datasets of acoustic power and magnetic flux, which are used to train LSTM models on predicting continuum intensity, 12 hours in advance. These novel machine learning (ML) models are able to capture variations of the acoustic power density associated with upcoming magnetic flux emergence and continuum intensity decrease. Testing of the models' performance was done on data for 5 ARs, unseen from the models during training. Model 8, the best performing model trained, was able to make a successful prediction of emergence for all testing active regions in an experimental setting and three of them in an operational. The model predicted the emergence of AR11726, AR13165, and AR13179 respectively 10, 29, and 5 hours in advance, and variations of this model achieved average RMSE values of 0.11 for both active and quiet areas on the solar disc. This work sets the foundations for ML-aided prediction of solar ARs.

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arXiv2024

Predicting the Emergence of Solar Active Regions Using Machine Learning

To create early warning capabilities for upcoming Space Weather disturbances, we have selected a dataset of 61 emerging active regions, which allows us to identify characteristic features in the evolution of acoustic power density to predict continuum intensity emergence. For our study, we have utilized Doppler shift and continuum intensity observations from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). The local tracking of 30.66 x 30.66-degree patches in the vicinity of active regions allowed us to trace the evolution of active regions starting from the pre-emergence state. We have developed a machine learning model to capture the acoustic power flux density variations associated with upcoming magnetic flux emergence. The trained Long Short-Term Memory (LSTM) model is able to predict 5 hours ahead whether, in a given area of the solar surface, continuum intensity values will decrease. The performed study allows us to investigate the potential of the machine learning approach to predict the emergence of active regions using acoustic power maps as input.

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arXiv2023

Spectro-Polarimetric Properties of Sunquake Sources in X1.5 Flare and Evidence for Electron and Proton Beam Impacts

The first significant sunquake event of Solar Cycle 25 was observed during the X1.5 flare of May 10, 2022, by the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory. We perform a detailed spectro-polarimetric analysis of the sunquake photospheric sources, using the Stokes profiles of the FeI 6173A line, reconstructed from the HMI linear and circular polarized filtergrams. The results show fast variations of the continuum emission with rapid growth and slower decay lasting 3-4 min, coinciding in time with the hard X-ray impulses observed by the Konus instrument onboard the Wind spacecraft. The variations in the line core appeared slightly ahead of the variations in the line wings, showing that the heating started in the higher atmospheric layers and propagated downward. The most significant feature of the line profile variations is the transient emission in the line core in three of the four sources, indicating intense, impulsive heating in the lower chromosphere and photosphere. In addition, the observed variations of the Stokes profiles reflect transient and permanent changes in the magnetic field strength and geometry in the sunquake sources. Comparison with the radiative hydrodynamics models shows that the physical processes in the impulsive flare phase are substantially more complex than those predicted by proton and electron beam flare models currently presented in the literature.

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arXiv2022

Analysis and Modeling of High-Frequency Emission and Deep Seismic Sources of Sunquakes

Recent work published by Lindsey et al find evidence for a deep and compact seismic source for the sunquake associated with the 2011 July 30 M9.3 flare, as well as seismic emission extending up to 10 mHz. We examine the sunquake independently, and a possible wavefront is found in the 8 mHz band, though no wavefront is easily discernible in the 10 mHz band. Additionally, we perform numerical simulations of seismic excitation modeled with the reported parameters and changes in the power spectra with increasing depth of the excitation source are examined. It is found that the peak frequency decreases for increasing depths, but a shallow minimum is indicated between z=0 and z=-840 km. Analysis of the suspected wavefront of the M9.3 sunquake finds that the power spectrum of the reported seismic emission is close to that of background oscillations, though with a peak frequency noticeably lower than the background peak. Additionally, it is found that the amplitude of the source estimated by Lindsey et al is too low to produce the observed wavefront.

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arXiv2022

Detection of Travel Time Anisotropy from Subsurface Horizontal Magnetic Fields

A time-distance measurement technique is derived to isolate phase travel time anisotropy caused by subsurface horizontal magnetic fields, and a method which uses the measured anisotropy to estimate the field's orientation is also derived. A simulation of acoustic waves propagating in a uniform, inclined magnetic field with solar background structure is used to verify the derived technique. Then, the procedure is applied to a numerical simulation of a sunspot, for which the subsurface state is known, to provide context for the results obtained from the study of several sunspots observed by the Helioseismic and Magnetic Imager. Significant anisotropies are detected, on the order of one minute, and the subsurface field's azimuth is estimated and compared with the azimuth of the surface magnetic field. In all cases, the subsurface azimuth is found to be well-aligned with that of the surface, and the results from the numerical simulation are used to interpret features in the detected travel time anisotropy.

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arXiv2021

Analysis of Time-Distance Helioseismology for Detection of Emerging Active Regions

A time-distance helioseismic technique, similar to the one used by Ilonidis et al (2011), is applied to two independent numerical models of subsurface sound-speed perturbations to determine the spatial resolution and accuracy of phase travel time shift measurements. The technique is also used to examine pre-emergence signatures of several active regions observed by the Michelson Doppler Imager (MDI) and the Helioseismic Magnetic Imager (HMI). In the context of similar measurements of quiet sun regions, three of the five studied active regions show strong phase travel time shifts several hours prior to emergence. These results form the basis of a discussion of noise in the derived phase travel time maps and possible criteria to distinguish between true and false positive detection of emerging flux.

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arXiv2020

Estimation of Key Sunquake Parameters through Hydrodynamic Modeling and Cross-Correlation Analysis

Sunquakes are one of the more distinct secondary phenomena related to solar flares, where energy deposition in the lower layers of the Sun's atmosphere excites acoustic waves easily visible in Helioseismic and Magnetic Imager (HMI) dopplergrams. We explore two possible sources of sunquakes in the context of the electron beam hypothesis: an instantaneous transfer of momentum and a gradual applied force due to flare eruption. We model the sunquake excitation and compare with five observed sunquake events using a cross-correlation analysis. We find that at least half the events studied are consistent with the electron beam hypothesis and estimate the energy required to excite the sunquakes to be within the range determined by previous studies.

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